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Multiple spheres detection problem-Center based clustering approach
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DOI：10.1016/j.patrec.2023.10.018.png)
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In this paper, we propose an adaptation of the well-known k-means algorithm for solving the multiple spheres detection problem when data points are homogeneously scattered around several spheres. We call this adaptation the k-closest spheres algorithm. In order to choose good initial spheres, we use a few iterations of the global optimizing algorithm DIRECT, resulting in the high efficiency of the proposed k-closest spheres algorithm. We present illustrative examples for the case of non-intersecting and for the case of intersecting spheres. We also show a real-world application in analyzing earthquake depths.
Keyword:
Multiple spheres detection
k-means algorithm
k-closest spheres algorithm
DIRECT algorithm
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